For a long time, scientists in the field of material science have researched, designed and tested various instruments that claimed to provide accurate service life prediction (“SLP”) using accelerated methods. Materials formulators or manufacturers desire to use short term laboratory test methods and apparatus to predict how specific material formulations will perform in an end-use environment before making investments in manufacturing and production and subsequent placement in such end-use environment. The short term laboratory testing needs to be done accurately in order to predict the service life of specific formulations. With such testing, materials scientists can disqualify poor performing material formulations and focus research and design assets (time, money, etc.) on only good performing candidate material formulations. Additionally, material scientists can refrain from costly “overly engineered” materials formulations for specific end uses. In this way, accurate accelerated SLP methods and apparatus can allow the material scientist to look into the future and see how a material will perform under the action of long term weathering degradation processes before actually subjecting a material to years and years of outdoor weathering in an end-use environment.
Currently, there have been long felt and un-met needs in the material science industry to develop an accurate SLP methods and apparatus that faithfully predict material performance in selected or desired micro-environment cycles, notwithstanding the many scientific attempts that have been previously made. For example, the National Institute of Standards & Technology (“NIST”) SLP publications and SLP consortiums, leading materials manufacturers' research and development efforts, European and Asian SLP symposium efforts, etc. evidence and document this need as well as the sizeable body of general technical literature on this subject. There also exists a material testing industry commonly referred to as ‘weathering testing’ that produces instruments that use accelerated laboratory or artificial weathering approaches based on exposure conditions established by standards committees, such as ASTM, NIST, Society of Automotive Engineers (“SAE”), etc., in an attempt at SLP. Even more specifically, there is an American Society for Testing and Materials (“ASTM”) standard for SLP that clearly documents the current state of the art for accelerated artificial weathering SLP. Although the current state of the art offers some approaches for SLP, these approaches are found to be significantly and importantly lacking in accuracy and applicability because they fail to recreate desired or selected end-use environments actually experienced by the material. Typically, these approaches offer only qualitative or relative assessments (“good” vs. “poor” predicted performance) or relative ranking (formulation “A” should perform better than formulation “B” in the same end-use environment). Additionally, these approaches typically work in a limited sense for some materials but not for other materials. For example, one SLP approach may be relatively accurate for generally predicting polycarbonate yellowing outdoors (to the degree described herein), but cannot accurately predict to any degree nylon's mechanical properties changes due to end-use environments or be accurate for many other materials or properties.
These approaches provide only meager incremental improvements in SLP and still ultimately fail to accurately predict service life in actual end-use environments for nearly all materials. The solution to accurate SLP, therefore, remains not obvious.
Conventional artificial or laboratory weathering devices use a number of approaches in an attempt to provide meaningful information and attempt to solve the SLP problem. For example, it is conventional knowledge that much of the end-use environment material degradation is caused by solar ultra-violet (“UV”) energy degradation, so materials researchers have exposed materials to increased irradiance levels of UV. However, other end-use environment conditions also effect material degradation, such as temperature and moisture. Consequently, researchers also developed test approaches to simultaneously increase UV irradiance, temperature and moisture in weathering testing devices. Examples of conventional state of the art weathering approaches for SLP are set forth in the table below.
TABLE IASTM G 155 COMMON EXPOSURE CONDITIONSIRRADIANCE,CYCLEFILTERAPPROX.EXPOSURE CYCLE1Daylight0.35 W/m2/nm.102 min light at 63 (+−2.5)° C. Black Panel Temperature340 nm18 min light and water spray (air temp. not controlled)2Daylight0.35 W/m2/nm.102 min light at 63 (+−2.5)° C. Black Panel Temperature340 nm18 min light and water spray (air temp. not controlled);6 h at 95 (+−4.0)% RH, at 24 (+−2.5)° C. Black PanelTemperature3Daylight0.35 W/m2/nm.1.5 h light at 70 (+−5)% RH, at 77 (+−3)° C. Black Panel340 nmTemperature.5 h light and water spray (air temp. not controlled)4Window.30 W/m2/nm.100% light, 55 (+−5.0)% RH, at 55 (+−2.)° C. BlackGlass340 nmPanel Temperature5Window1.1 W/m2/nm.102 min light, 35 (+−5.0)% RH, at 63 (+−2.5)° C. BlackGlass420 nmPanel Temperature18 minutes light & water spray (air temp. not controlled)6Window1.10 W/m2/nm.3.8 h light at 35 (+−5.0)% RH, at 63 (+−2.5)° C. BlackGlass420 nmPanel Temperature1 h dark, 90 (+−5.0)% RH, at 43 (+−2)° C. Black PanelTemperature7Daylight0.55 W/m2/nm.40 min light, 50 (+−5.0)% RH, at 70 (+−2)° C. Black Panel340 nmTemperature20 min light and water spray on specimen face;60 min light, 50 (+−5.0)% RH, at 70 (+−2)° C. Black PanelTemperature;60 min dark and water spray on specimen back, 95 (+5.0)% RH, 38 (+−2)° C. Black Panel Temperature8Daylight0.55 W/m2/nm.3.8 h light, 50 (+− 5.0)% RH, at 89 (+− 3)° C. Black340 nmPanel Temperature1.0 h light, 95 (+−5.0)% RH, at 38 (+−3)° C. BlackPanel Temperature
The conventional approaches herein have been proven to offer only meager incremental improvements in SLP and still ultimately fail to accurately predict service life in actual end-use environments for most materials. The solution to accurate SLP, therefore, remains not obvious.
As may be observed from the table above, conventional artificial or laboratory weathering devices have simple control algorithms that monitor and maintain a temperature, irradiance or humidity at a single set point for a period of time. The duration of the specific variable and the absolute settings of the variable are typically determined by standards committees referenced in part above and as known by one of ordinary skill in the art. The ASTM standards for xenon arc and fluorescent weathering devices show the very simplistic cycles for different material tests. For example, ASTM G 154-06 sets forth in table X2.1 for fluorescent weathering devices a number of different cycles, all of which simply proscribe a number of exposure hours at a single irradiance and temperature and a number of hours of condensation at a single temperature. SAE J1960 sets forth suggested cycles such as 40 minutes of irradiance at 0.55 W/m2, at 70° C. black standard temperature followed by 20 minutes of irradiance at 0.55 W/m2, at 70° C. with a water spray on specimens, followed by another 60 min of irradiance at the same light and temperature settings, followed by 60 min of dark at 38° C. ASTM G 26 sets forth the same exposure cycle philosophy using specific static set points for specific durations of time. As further examples, FIG. 1 is a graphical representation of the step function of the ASTM G 155, cycle 8 irradiance exposure cycle, and FIG. 2 is a graphical representation of the step function of the ASTM G 155, cycle 8 temperature exposure cycle. These cycles were developed in consensus standards committees and have little resemblance to the end-use environment cycles they were intended to simulate.
These conventional approaches do not consider that the natural end-use environment has significantly different cycles than could be produced by conventional artificial or laboratory weathering devices. Cycles observed in the natural end-use environment are analog in nature (typically sinusoidal-like) rather than step functions as used by conventional approaches and devices. Because of such differences, obtaining good correlation between the two exposure results (i.e., artificial versus natural end-use environments) is very difficult or impossible for many types of materials and products. The reason for this is that the conventional exposure simulation in the laboratory weathering device with an artificial light source poorly simulates the end-use environment variable exposure cycles, and as a result poorly simulates the degradation effects observed on such materials and products in end-use environments. Therefore, material exposure tests using conventional artificial weathering device cycles set by standards committees fail to achieve accurate service life prediction of materials exposed to end-use environment cycles.
Conventional artificial weathering approaches also do not account for reciprocity effects in material degradation. Deviations from reciprocity often occur in materials when exposure at a low irradiance results in a different effect than irradiance at higher levels even when the exposure results in the same radiant energy, as further described in US Publication No. 2005/0120811 A1, which is incorporated herein by reference. Conventional artificial weathering approaches and devices use exposures timed on a UV radiant energy basis (the product of UV irradiant intensity and time) with irradiance set at a single level or step measured in J/m2 UV. Likewise, end-use exposures are also timed and measured by UV radiant energy. However, this is an erroneous approach to SLP, because the cumulative degradation effect from a natural end-use environment cycle of varying UV intensity will be very different than the cumulative degradation effect observed in an artificial weathering device from an artificial cycle at a single UV intensity even though both the exposures are conducted to the same aggregate amount of UV radiant energy exposure. Difficulty in obtaining the same degradation results with identical materials exposed for the same aggregate UV radiant exposure regardless of artificial exposure or natural exposure points to a major disadvantage with the conventional approach.
Co-variables with light intensity, material temperature and moisture also differ significantly between conventional artificial weathering approaches and observed end-use environment cycles. Material exposure temperatures are a complex function of material characteristics such as solar absorbance, emittance and thermal conductivity characteristics of the material as well as environmental variable characteristics such as ambient temperature, wind velocity, solar intensity, sky temperature and material orientation characteristics. Because the end-use environment variable characteristics are always changing, the dynamic nature of ever-changing environmental variables results in very different material degradation observed in end-use environments compared with observations in artificial weathering approaches and devices which hold exposures at fixed, step function set points. For example, it is well known that varying the temperature of reacting materials can vary chemical reaction rates. A dynamic end-use temperature environment, therefore, can be expected to produce a different cumulative material degradation than conventional artificial laboratory weathering approaches or devices that hold a single temperature step function.
Exposure temperature is a co-variable with light intensity; accordingly, there is an opportunity for a meta-level interaction between reciprocity effects and chemical reaction rates affected by temperature. Temperature and moisture variables also interact given that diffusion rates are controlled by temperature. Therefore, moisture ingress into materials on natural exposures are a complex function of environmental moisture (rain, condensation, humidity, etc.), and material temperature, which, in turn is a complex function of solar irradiant intensity interacting with ambient temperatures and other environmental variables. The buildup and interplay of lower and higher order variable effects on material degradation occurring in the natural diurnal and seasonal end-use environment cycles cannot be simulated by simple, single set point step function settings in conventional artificial weathering devices or operational approaches.
Therefore, there is a need for new and non-obvious methods and apparatus for accurate service life prediction of materials that do not require exposure cycles that have little resemblance to the natural end-use environment cycles they were intended to simulate; have difficulty in obtaining the same degradation results with identical materials; work in a limited sense for some materials but not at all for other materials; have a cumulative degradation effect very different than the cumulative degradation effect observed from a natural end-use environment cycle; fail to account for the buildup and interplay of lower and higher order variable effects on material degradation occurring in the natural diurnal and seasonal end-use environment cycles; rudimentary operating approaches, such as, fixed step functions that are unrelated to natural end-use environment cycles.
The subject disclosure is directed to a new, non-obvious and improved methods and apparatus that overcome all of the herein identified problems and disadvantages, and others, and provides an optimal approach for accurate SLP methods and apparatus that faithfully predict material performance in selected or desired micro-environment cycles and faithfully reproduce selected or desired micro-environment cycle characteristics.